mlsanityData to 14 Oct 2026

A Deep User Interface for Exploring LLaMa

arXiv 2502.20938 ↗First posted 28 Feb 2025cs.HC cs.AIcited by 0

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Abstract (arXiv)

The growing popularity and widespread adoption of large language models (LLMs) necessitates the development of tools that enhance the effectiveness of user interactions with these models. Understanding the structures and functions of these models poses a significant challenge for users. Visual analytics-driven tools enables users to explore and compare, facilitating better decision-making. This paper presents a visual analytics-driven tool equipped with interactive controls for key hyperparameters, including top-p, frequency and presence penalty, enabling users to explore, examine and compare the outputs of LLMs. In a user study, we assessed the tool's effectiveness, which received favorable feedback for its visual design, with particular commendation for the interface layout and ease of navigation. Additionally, the feedback provided valuable insights for enhancing the effectiveness of Human-LLM interaction tools.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 20 of its 45 references that are in the map. First posted on arXiv 28 Feb 2025.

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20 of 45 references.

References · 20

  1. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 14,132
  2. 2019Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AIcited by 1,552
  3. 2023Benchmarking Large Language Models for News Summarizationcited by 445
  4. 2022Pretrained Language Models for Text Generation: A Surveycited by 122
  5. 2019Human-AI Collaboration in Data Science: Exploring Data Scientists' Perceptions of Automated AIcited by 79
  6. 2019explAIner: A Visual Analytics Framework for Interactive and Explainable Machine Learningcited by 70
  7. 2022Enabling Conversational Interaction with Mobile UI using Large Language Modelscited by 66
  8. 2024Understanding LLMs: A Comprehensive Overview from Training to Inferencecited by 59
  9. 2020A Survey of Visual Analytics Techniques for Machine Learningcited by 56
  10. 2018Towards Explainable NLP: A Generative Explanation Framework for Text Classificationcited by 55
  11. 2024LLM Processes: Numerical Predictive Distributions Conditioned on Natural Languagecited by 55
  12. 2024Time Series Forecasting with LLMs: Understanding and Enhancing Model Capabilitiescited by 48
8 more
  1. 2024RareBench: Can LLMs Serve as Rare Diseases Specialists?cited by 45
  2. 2024LLM Comparator: Visual Analytics for Side-by-Side Evaluation of Large Language Modelscited by 29
  3. 2018The State of the Art in Integrating Machine Learning into Visual Analyticscited by 24
  4. 2024Exploring the Capability of LLMs in Performing Low-Level Visual Analytic Tasks on SVG Data Visualizationscited by 18
  5. 2024Beware of Words: Evaluating the Lexical Diversity of Conversational LLMs using ChatGPT as Case Studycited by 10
  6. 2020HyperTendril: Visual Analytics for User-Driven Hyperparameter Optimization of Deep Neural Networkscited by 7
  7. 2024StuGPTViz: A Visual Analytics Approach to Understand Student-ChatGPT Interactionscited by 7
  8. 2024iScore: Visual Analytics for Interpreting How Language Models Automatically Score Summariescited by 6

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